Semi-Supervised Learning under a Mixed-Missingness Mechanism in Finite Mixture Models

Documentation for package ‘SSLfmm’ version 0.1.0

bayesclassifier	Bayes' Rule Classifier
compute_d2	Squared Discriminant Score for Two-Group LDA (Equal Covariance)
EM_FMM_SemiSupervised	EM for Semi-Supervised FMM with a Mixed-Missingness Mechanism (MCAR + entropy-based MAR)
EM_FMM_SemiSupervised_Complete_Initial	Complete-Data Warm-Up Initialization for Semi-Supervised FMM with a Mixed-Missingness Mechanism
EM_FMM_SemiSupervised_Initial	Quick Initializer for alpha, xi, and Mixture Parameters
error_beta_classification	Compute Theoretical Bayes' Error for a Binary Gaussian Mixture
get_clusterprobs	Posterior Cluster Probabilities for a Gaussian Mixture
get_entropy	Per-Row Entropy of Posterior Cluster Probabilities
initialestimate	Initialize Parameters for a FMM from Labeled Subset
logsumexp	Numerically Stable Log-Sum-Exp
neg_loglik	Negative Log-Likelihood for Semi-Supervised FMM with a Mixed-Missingness Mechanism
normalise_logprob	Normalise Log-Probabilities
pack_theta	Pack FMM Parameters into a Vector
rmix	Draw from a Gaussian Mixture Model
simulate_mixed_missingness	Simulate a Gaussian Mixture Dataset with a Mixed-Missingness Mechanism (MAR + MCAR)
unpack_theta	Unpack FMM Parameter Vector